Credit Rating System

From Open Risk Manual


Credit Rating System denotes a set of tools and methodologies that assist with the creation of Credit Risk metrics, which in turn assist with the Risk Management of credit portfolios. The objective or a rating system is to rank borrowers systematically with meaningful credit risk quality differentiation


A credit rating system will include a number of components depending on the complexity and scope of its application. For example

Issues and Challenges

  • It is very common that that rating system is fundamentally based on the probability of default of borrowers, but credit loss rating systems are also possible. Comparisons between such different design systems can be fraught with difficulties (additional assumptions and Credit Rating Philosophy differences)
  • The construction of rating systems enables significant differences in how they respond to the fluctuations of economic activity. This is know as the Point-in-time versus Through-the-cycle difference.
  • While many aspects of credit rating systems are algorithmic / automated, human judgement may play a significant role. In this case for regulated firms there are specific additional requirements[1]
  • Credit markets make extensive use of various forms of explicit Financial Guarantee contracts or implicit guarantees. Those must be reflected accurately in the adjusted ratings

ECB TRIM Requirements

Human Judgement

Institutions must have specific definitions, processes and criteria for assigning exposures to grades or pools. The grade and pool definitions must be sufficiently detailed. To comply with this provision, institutions should ensure that, when human judgement is used in the assignment of exposures to grades or pools, there is a framework in place that establishes clear and detailed guidelines and procedures on the application of human judgement (e.g. through the use of pre-defined questionnaires).

The use of human judgement should be documented in a way that ensures the rating assignment can be understood and replicated by a third party.

When human judgement is used for the purpose of risk differentiation, for example in the setting of the model’s assumptions, the identification of risk drivers and determination of their weights, or the identification and combination of model components, there is a risk of the model-based assignments being inaccurate. To mitigate this risk, institutions should ensure that the incorporation of human judgement is appropriately managed and proportionate to the number of available observations

The results of the statistical model must be complemented by human judgement, especially by taking into account all information not included in the model. The higher the number of relevant observations, the more the institutions should rely on the outcomes of the statistical model.

For the purposes of quantifying the risk parameters to be associated to grades or pools, estimates must not be based purely on judgemental considerations.To this end, where human judgement is used to a greater extent because of the ow number of available internal observations, institutions should apply a higher MoC to their estimates to account for additional uncertainty.

In addition, whenever human judgement is used in the estimation of risk parameters (for either risk differentiation or risk quantification purposes) institutions are expected to have in place a framework under paragraph 35 of the EBA GL on PD and LGD.


  1. ECB guide to internal models - Credit Risk, Sep 2018

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